Abstract
This paper sheds some light on the effects of social capital variables (social network data, physical appearance, etc.) on loan-to-value (LTV), a crucial variable to evaluate systemic risk. Using a unique database created by merging several sources of data, we show that the introduction of social capital variables are shown to be statistically significantly related to LTV. In particular, Facebook likes in a month and creditworthiness are a negative determinant of LTV while beauty and certain personality traits play a role in borrowers obtaining a higher LTV. We distinguish these effects depending on the LTV variable used: loan-to-appraisal (entirely under the control of lender) and loan-to-transaction (in which the transaction price can also be influenced). As policy implications we found that social capital variables capture information that would otherwise be unobservable using only the traditional variables in the sense that they are related to information lenders may have at lending that the researchers do not observe.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
